In recent years, reconnaissance, surveillance, disaster relief, search and rescue, agriculture information gathering and fast remote sensing mapping has gained increasingly attentions in civilian and military purposes. For example, due to their small size and low-cost sensor platform, Unmanned Aerial Vehicle (UAV) can be an attractive platform for executing such operations. However, UAV introduces some significant challenges when used in surveillance systems. For an instance, the background significantly changes as the camera has a fast motion and an irregular rotation, and the motion of a UAV vehicle is usually not smooth. Further, frame rate is very low (for example, 1 frame per second) so as to increase the difficulties of detecting and tracking ground moving targets, and small object size will bring another challenge for object detection and tracking. Also, a camera's strong illumination change and stripe noise can create some hard problems to separate true moving objects from the background.
Existing approaches also include object initialization issues, and are additionally unable to obtain high-accuracy registration results, to handle rotation and scale variation of a target, and to deal with similar distribution between target and background.